Cárdenes R, Zhang C, Klementieva O, Werner S, Guttmann P, Pratsch C, Cladera J, Bijnens B. 3D Membrane Segmentation and Quantification of Intact Thick Cells using Cryo Soft X-ray Transmission Microscopy: A Pilot Study. PLoS ONE 12(4): e0174324
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Cárdenes R, Zhang C, Klementieva O, Werner S, Guttmann P, Pratsch C, Cladera J, Bijnens B. 3D Membrane Segmentation and Quantification of Intact Thick Cells using Cryo Soft X-ray Transmission Microscopy: A Pilot Study. PLoS ONE 12(4): e0174324
Cárdenes R, Zhang C, Klementieva O, Werner S, Guttmann P, Pratsch C, Cladera J, Bijnens B. 3D Membrane Segmentation and Quantification of Intact Thick Cells using Cryo Soft X-ray Transmission Microscopy: A Pilot Study. PLoS ONE 12(4): e0174324
doi:10.1371/journal.pone.0174324
Structural analysis of biological membranes is important for understanding cell and sub-cellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10μm) with details of sub-cellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis.
Additional material:
- Evaluation dataset: https://zenodo.org/record/259703